---
title: "Reference: Content Similarity | Evals | Kastrax Docs"
description: Documentation for the Content Similarity Metric in Kastrax, which measures textual similarity between strings and provides a matching score.
---

# ContentSimilarityMetric ✅

The `ContentSimilarityMetric` class measures the textual similarity between two strings, providing a score that indicates how closely they match. It supports configurable options for case sensitivity and whitespace handling.

## Basic Usage ✅

```typescript
import { ContentSimilarityMetric } from "@kastrax/evals/nlp";

const metric = new ContentSimilarityMetric({
  ignoreCase: true,
  ignoreWhitespace: true
});

const result = await metric.measure(
  "Hello, world!",
  "hello world"
);

console.log(result.score); // Similarity score from 0-1
console.log(result.info); // Detailed similarity metrics
```

## Constructor Parameters ✅

<PropertiesTable
  content={[
    {
      name: "options",
      type: "ContentSimilarityOptions",
      description: "Configuration options for similarity comparison",
      isOptional: true,
      defaultValue: "{ ignoreCase: true, ignoreWhitespace: true }",
    }
  ]}
/>

### ContentSimilarityOptions

<PropertiesTable
  content={[
    {
      name: "ignoreCase",
      type: "boolean",
      description: "Whether to ignore case differences when comparing strings",
      isOptional: true,
      defaultValue: "true",
    },
    {
      name: "ignoreWhitespace",
      type: "boolean",
      description: "Whether to normalize whitespace when comparing strings",
      isOptional: true,
      defaultValue: "true",
    }
  ]}
/>

## measure() Parameters ✅

<PropertiesTable
  content={[
    {
      name: "input",
      type: "string",
      description: "The reference text to compare against",
      isOptional: false,
    },
    {
      name: "output",
      type: "string",
      description: "The text to evaluate for similarity",
      isOptional: false,
    }
  ]}
/>

## Returns ✅

<PropertiesTable
  content={[
    {
      name: "score",
      type: "number",
      description: "Similarity score (0-1) where 1 indicates perfect similarity",
    },
    {
      name: "info",
      type: "object",
      description: "Detailed similarity metrics",
      properties: [
        {
          type: "number",
          parameters: [
            {
              name: "similarity",
              type: "number",
              description: "Raw similarity score between the two texts",
            }
          ]
        }
      ]
    },
  ]}
/>

## Scoring Details ✅

The metric evaluates textual similarity through character-level matching and configurable text normalization.

### Scoring Process

1. Normalizes text:
   - Case normalization (if ignoreCase: true)
   - Whitespace normalization (if ignoreWhitespace: true)

2. Compares processed strings using string-similarity algorithm:
   - Analyzes character sequences
   - Aligns word boundaries
   - Considers relative positions
   - Accounts for length differences

Final score: `similarity_value * scale`

### Score interpretation
(0 to scale, default 0-1)
- 1.0: Perfect match - identical texts
- 0.7-0.9: High similarity - mostly matching content
- 0.4-0.6: Moderate similarity - partial matches
- 0.1-0.3: Low similarity - few matching patterns
- 0.0: No similarity - completely different texts

## Example with Different Options ✅

```typescript
import { ContentSimilarityMetric } from "@kastrax/evals/nlp";

// Case-sensitive comparison
const caseSensitiveMetric = new ContentSimilarityMetric({
  ignoreCase: false,
  ignoreWhitespace: true
});

const result1 = await caseSensitiveMetric.measure(
  "Hello World",
  "hello world"
); // Lower score due to case difference

// Example output:
// {
//   score: 0.75,
//   info: { similarity: 0.75 }
// }

// Strict whitespace comparison
const strictWhitespaceMetric = new ContentSimilarityMetric({
  ignoreCase: true,
  ignoreWhitespace: false
});

const result2 = await strictWhitespaceMetric.measure(
  "Hello   World",
  "Hello World"
); // Lower score due to whitespace difference

// Example output:
// {
//   score: 0.85,
//   info: { similarity: 0.85 }
// }
```

## Related ✅

- [Completeness Metric](./completeness)
- [Textual Difference Metric](./textual-difference) 
- [Answer Relevancy Metric](./answer-relevancy)
- [Keyword Coverage Metric](./keyword-coverage)